Articles | Volume 28, issue 1
Nonlin. Processes Geophys., 28, 23–41, 2021
https://doi.org/10.5194/npg-28-23-2021
Nonlin. Processes Geophys., 28, 23–41, 2021
https://doi.org/10.5194/npg-28-23-2021

Research article 15 Jan 2021

Research article | 15 Jan 2021

Fast hybrid tempered ensemble transform filter formulation for Bayesian elliptical problems via Sinkhorn approximation

Sangeetika Ruchi et al.

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Jana de Wiljes on behalf of the Authors (09 Oct 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (12 Oct 2020) by Olivier Talagrand
RR by Marc Bocquet (14 Oct 2020)
RR by Femke Vossepoel (02 Nov 2020)
ED: Publish subject to minor revisions (review by editor) (06 Nov 2020) by Olivier Talagrand
AR by Svenja Lange on behalf of the Authors (16 Nov 2020)  Author's response
ED: Publish as is (16 Nov 2020) by Olivier Talagrand
AR by Jana de Wiljes on behalf of the Authors (19 Nov 2020)  Author's response    Manuscript

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Jana de Wiljes on behalf of the Authors (12 Jan 2021)   Author's adjustment   Manuscript
EA: Adjustments approved (14 Jan 2021) by Olivier Talagrand
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Short summary
To infer information of an unknown quantity that helps to understand an associated system better and to predict future outcomes, observations and a physical model that connects the data points to the unknown parameter are typically used as information sources. Yet this problem is often very challenging due to the fact that the unknown is generally high dimensional, the data are sparse and the model can be non-linear. We propose a novel approach to address these challenges.